Objective Bayesian Nets for Systems Modelling and Prognosis in Breast Cancer

  • Sylvia Nagl
  • Matt Williams
  • Jon Williamson
Part of the Studies in Computational Intelligence book series (SCI, volume 156)


Cancer treatment decisions should be based on all available evidence. But this evidence is complex and varied: it includes not only the patient’s symptoms and expert knowledge of the relevant causal processes, but also clinical databases relating to past patients, databases of observations made at the molecular level, and evidence encapsulated in scientific papers and medical informatics systems. Objective Bayesian nets offer a principled path to knowledge integration, and we show in this chapter how they can be applied to integrate various kinds of evidence in the cancer domain. This is important from the systems biology perspective, which needs to integrate data that concern different levels of analysis, and is also important from the point of view of medical informatics.


Breast Cancer Bayesian Network Argumentation Framework Maximum Entropy Principle Constraint Graph 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Sylvia Nagl
    • 1
  • Matt Williams
    • 2
    • 3
  • Jon Williamson
    • 4
  1. 1.Department of OncologyUniversity College LondonLondonUK
  2. 2.Advanced Computation LaboratoryCancer Research UKUK
  3. 3.Computer ScienceUniversity College LondonLondonUK
  4. 4.Department of PhilosophyUniversity of KentKentUK

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